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Data-driven IT resource planning: Take control of ever-growing software maintenance costs

For many IT-intensive enterprises, the bloating cost of maintaining software applications may be the biggest elephant in the room. Software maintenance costs typically comprise up to 75% of the total cost of ownership of each application. With so much investment and energy dedicated to keeping the lights on, finding a way to better allocate IT resources — even just by a marginal amount — can have significant impact on the enterprise’s capacity to innovate.

CAST’s research into this area has uncovered some provocative findings. As we’ve discussed previously on the On Quality blog, the cost of maintaining a software application is directly proportional to its size and complexity. IT organizations can take several steps using static code quality analysis to reduce size and complexity, and thus diminish their software maintenance costs.

We’ve taken this a step further, and CAST just announced a new software maintenance estimation in CAST Highlight, our application portfolio analysis SaaS platform. On top of assessing the size, software risk and complexity of custom applications across an organization’s entire portfolio, CAST Highlight now provides insight into the effort required to maintain each system. Based on the widely used COCOMO® II cost estimation engine, CAST Highlight’s estimate helps IT management identify which systems are disproportionately draining the maintenance budget, and enables leadership to get better insight into resourcing requirements to improve planning and budgeting.

Unlike traditional resource planning, which often times suffers from a lack of reliable data, CAST Highlight’s method delivers a quantified measure backed by a trusted industry model. IT organizations can use the estimation as an input for adjusting their resource allocations, and ultimately route investment to innovation. View this infographic and see how a data-driven approach to IT resource planning compares to traditional methods.